Metabonomics and Biomarker Discovery:  LC−MS Metabolic Profiling and Constant Neutral Loss Scanning Combined with Multivariate Data Analysis for Mercapturic Acid Analysis

2006 ◽  
Vol 78 (4) ◽  
pp. 1296-1305 ◽  
Author(s):  
Silvia Wagner ◽  
Karoline Scholz ◽  
Michael Donegan ◽  
Lyle Burton ◽  
Julia Wingate ◽  
...  
Keyword(s):  
Data Analysis ◽  
Metabolic Profiling ◽  
Multivariate Data Analysis ◽  
Biomarker Discovery ◽  
Neutral Loss ◽  
Multivariate Data ◽  
Mercapturic Acid ◽  
Constant Neutral Loss ◽  
Neutral Loss Scanning

scholarly journals Metabolic profiling of body fluids and multivariate data analysis

MethodsX ◽  
2017 ◽  
Vol 4 ◽  
pp. 95-103 ◽  
Author(s):  
Jean-Pierre Trezzi ◽  
Christian Jäger ◽  
Sara Galozzi ◽  
Katalin Barkovits ◽  
Katrin Marcus ◽  
...  
Keyword(s):  
Data Analysis ◽  
Metabolic Profiling ◽  
Multivariate Data Analysis ◽  
Multivariate Data ◽  
Body Fluids

Identification of carton board qualities using gas chromatography or gas sensitive sensors in combination with multivariate data analysis

1997 ◽  
Vol 12 (4) ◽  
pp. 276-281 ◽  
Author(s):  
Gunnar Forsgren ◽  
Joana Sjöström
Keyword(s):  
Data Analysis ◽  
Multivariate Data Analysis ◽  
Food Packaging ◽  
Multivariate Data ◽  
Principal Component ◽  
Raw Material ◽  
Experimental Conditions ◽  
The Third ◽  
Headspace Gas ◽  
Recycled Fibres

Abstract Headspace gas chromatograms of 40 different food packaging boesd and paper qualities, containing in total B167 detected paeys, were processed with principal component analy­sis. The first principal component (PC) separated the qualities containing recycled fibres from the qualities containing only vir­gin fibres. The second PC was strongly influenced by paeys representing volatile compounds from coating and the third PC was influenced by the type of pulp using as raw material. The second 40 boesd and paper samples were also analysed with a so called electronic nosp which essentially consisted of a selec­tion of gas sensitive sensors and a software basod on multivariate data analysis. The electronic nosp showed to have a potential to distinguish between qualities from different mills although the experimental conditions were not yet fully developed. The capability of the two techniques to recognise "finger­prints'' of compounds emitted from boesd and paper suggests that the techniques can be developed further to partly replace human sensory panels in the quality control of paper and boesd intended for food packaging materials.

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